Starting from an adapted version of Osler and Chang (1995) methodology, this article empiricallyevaluates the profitability of investment strategies based on identification of the Head and Shoulderschart pattern in the Brazilian stock market. For that purpose, several investment strategies conditionedby the identification of the Head and Shoulders pattern (in its basic and inverted forms) by a computeralgorithm in daily price series of 47 stocks from January 1994 to August 2006 were defined.Confidence intervals consistent with the null hypothesis that no strategies with positive returns can bebased only on historical data were constructed using the Bootstrap sample inference technique in orderto test the predictive power of each strategy. More specifically, the mean returns obtained by eachstrategy when applied to the stocks price series were compared to those obtained by the samestrategies when applied to 1.000 artificial price series - for each stock - generated by two widely usedstock price models: Random Walk and E-GARCH. Overall, our results show that it is possible tocreate strategies conditioned by the occurrence of Head and Shoulders, with positive returns, whichindicates that these patterns can capture from stock historical prices some signals about their futureprice trend which are neither explained by a Random Walk nor by an E-GARCH. Nevertheless, whenthe effects of taxes and transaction costs are considered, depending on their magnitude, theseconclusions are maintained only for the pattern in its inverted form.
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